Communication-prompted user assistance

ABSTRACT

Communications are monitored for user intentions related to user tasks such as meeting scheduling and the like  308 . When an intention (e.g. mention of a meeting) is determined from the communications, candidate task actions (e.g., scheduling meeting) are initiated and/or stored  310 . At an appropriate event trigger (e.g. completion of communications), a user can be prompted with a list of candidate task actions and can select which actions to perform  312 . Action profiles  320  can also be incorporated to allow customization of how task actions are completed. These profiles can be called at the time of task action execution to guide the action fulfillment. The profiles can be user and/or system generated and/or provided by third parties and the like. The task actions are typically performed utilizing task related applications to fully execute the task action so that additional user input is not required.

BACKGROUND

With the introduction of mobile communication devices, people havebecome quite accustomed to communicating with others at any place andtime. Thus, a user can discuss activities that are scheduled for afuture time but not be in a position to take note of the activity or itsdate. For example, an employee can be on their way to work when theyreceive an important call on their mobile phone from their boss. Theboss can inform them that there are several meetings today and duringthe week. The employee agrees to support these meetings, but due to adesire not to keep their boss online too long, they do not inform himthat they need to stop, find a pen and paper and write down the timesand dates of the meetings.

Instead, the employee attempts to memorize the meeting schedules andwrite them down when they arrive at the office. Depending on the numberof meetings and dates, this can likely lead to a forgotten meeting andassociated ramifications. In other scenarios, people are oftenpre-occupied with other interests while communicating and do not evenrealize that they have agreed to perform a task. For example, ateenager, while listening to music, attempts to hold a conversation withtheir parent and agrees to take out the garbage and clean up their room.This part of the conversation is typically quickly forgotten unlessreminded by the parent after the fact. Thus, often, especially in casualconversations, people forget or remember incorrectly tasks that theyhave mentioned or agreed to do. The ramifications of forgetting thesetasks can range from a minor inconvenience (teenager yelled at by theirparents) to a major impact (employee forgets client meeting and loseslarge client for business).

SUMMARY

Communications are monitored for user intentions related to user tasks.When an intention is determined from the communications, candidate taskactions are initiated and/or stored. A user can also be cued that acandidate task action has occurred. At an appropriate event trigger, auser can be prompted with a list of candidate task actions and canselect which actions to perform. Other instances can automaticallyperform candidate task actions without user intervention. Actionprofiles can also be incorporated to allow customization of how taskactions are performed. These profiles can be called at the time of taskaction execution to guide the action fulfillment. The profiles can beuser and/or system generated and/or provided by third parties and thelike. The task actions typically employ task related applications tofully execute the task action so that additional user input is notrequired. In other instances, communications details are attached to anexecuted task as a reminder to a user why the task was performed.

The above represents a simplified summary of the subject matter in orderto provide a basic understanding of some aspects of subject matterembodiments. This summary is not an extensive overview of the subjectmatter. It is not intended to identify key/critical elements of theembodiments or to delineate the scope of the subject matter. Its solepurpose is to present some concepts of the subject matter in asimplified form as a prelude to the more detailed description that ispresented later.

To the accomplishment of the foregoing and related ends, certainillustrative aspects of embodiments are described herein in connectionwith the following description and the annexed drawings. These aspectsare indicative, however, of but a few of the various ways in which theprinciples of the subject matter may be employed, and the subject matteris intended to include all such aspects and their equivalents. Otheradvantages and novel features of the subject matter may become apparentfrom the following detailed description when considered in conjunctionwith the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a task recognition system forcommunications in accordance with an aspect of an embodiment.

FIG. 2 is another block diagram of a task recognition system forcommunications in accordance with an aspect of an embodiment.

FIG. 3 is yet another block diagram of a task recognition system forcommunications in accordance with an aspect of an embodiment.

FIG. 4 is an example architecture of a task recognition system forcommunications in accordance with an aspect of an embodiment.

FIG. 5 is a flow diagram of a method of facilitating task recognition incommunications in accordance with an aspect of an embodiment.

FIG. 6 is another flow diagram of a method of facilitating taskrecognition in communications in accordance with an aspect of anembodiment.

FIG. 7 illustrates an example operating environment in which anembodiment can function.

DETAILED DESCRIPTION

The subject matter is now described with reference to the drawings,wherein like reference numerals are used to refer to like elementsthroughout. In the following description, for purposes of explanation,numerous specific details are set forth in order to provide a thoroughunderstanding of the subject matter. It may be evident, however, thatsubject matter embodiments may be practiced without these specificdetails. In other instances, well-known structures and devices are shownin block diagram form in order to facilitate describing the embodiments.

As used in this application, the term “component” is intended to referto a computer-related entity, either hardware, a combination of hardwareand software, software, or software in execution. For example, acomponent may be, but is not limited to being, a process running on aprocessor, a processor, an object, an executable, a thread of execution,a program, and/or a computer. By way of illustration, both anapplication running on a server and the server can be a computercomponent. One or more components may reside within a process and/orthread of execution and a component may be localized on one computerand/or distributed between two or more computers.

Communication devices that allow extreme mobility are becoming verycommonplace. While this allows for complete freedom of movement forusers, it can also encumber the user's ability to adequately take notesduring the communications. Tasks that are mentioned duringcommunications are soon forgotten or incorrectly remembered. Forexample, a business person can call a client and discuss meeting dates,purchases, and information requests (i.e., tasks) during the call.However, if the business person is not able to take notes during thecall, they might not fully remember all of the tasks discussed.Instances provided herein monitor communications to dynamicallyrecognize intentions of a user related to tasks mentioned incommunications. By utilizing intentions related to a task, an instancecan provide a candidate task action list for tasks in which the userdesires to participate. In some instances, a determination can be madeduring the communications as to whether a user wants to participate in atask. This information can then be used to automatically exclude thattask from the candidate task action list.

In FIG. 1, a block diagram of a task recognition system 100 forcommunications in accordance with an aspect of an embodiment is shown.The task recognition system 100 is comprised of a task assistantcomponent 102 that receives communications 104 and provides candidatetasks 106. The communications 104 can include, but are not limited to,voice communications and/or written communications and the like such as,for example, emailing, instant messaging, text messaging, telephonecalls, etc. The task assistant component 102 can be adapted to performvarious types of recognition based on the type of communications 104.The task assistant component 102 can employ artificial intelligencemechanisms to facilitate task recognition as well. The task assistantcomponent 102 monitors the communications 104 dynamically to extract auser's intent with regard to a task mentioned in the communications 104.For this type of processing, natural language techniques can be utilizedto facilitate in interpreting the user's intent.

Recognizing tasks alone in the communications 104 does not necessarilyyield the true intentions of a user. It is possible that a user can say,“please schedule a meeting at 10 am today,” and another user can reply,“no, I will not do that.” In that case, the intent of the second user isnot to schedule a meeting (the task). By incorporating task intent intothe dynamic monitoring, the task assistant component 102 can moreaccurately accumulate desirable candidate tasks 106. These candidatetasks 106 can then be presented to a user as a reminder of mentionedtasks during the communications 104. The user then can have the optionof dismissing the task prompts and/or selecting which tasks can beexecuted.

Instances of the task recognition system 100 can reside on acommunication device and/or reside in disparate locations from thecommunication device in distributed implementations. Considerations forthe location of components of a distributed system can include, but arenot limited to, available processing power (e.g., a cell phone might nothave enough processing power to perform natural language processing),communication device independent operation (e.g., monitoring performedas a service at a wireless cell provider rather than on a particularcell phone-avoiding device unique applications, etc.), and/orcommunication device functionality limitations (e.g., a dumbcommunication terminal without any significant processing capabilitiesand/or not supportable with applications) and the like. This type offlexibility allows easy introduction of the task recognition system 100into existing communication systems. By offering it to users as aservice first, users can become accustomed to its use without buying newcommunication devices and/or downloading additional applications and thelike. As newer and better communication devices evolve, more and morerelated components could be moved to individual communication devices.

It can also be appreciated that users can exploit instances providedherein to involve other parties not privy to the originalcommunications. For example, a traveling salesperson can take orders,promise product support, and/or offer to provide additional informationwhile communicating with a customer. Tasks associated with ordering canbe forwarded to an order processing department at the salesperson'sheadquarters so that it can be fulfilled quickly, tasks associated withproduct support can be forwarded to a technical support team so they cancontact the customer immediately, and/or tasks associated with supplyingadditional product information can be forwarded to the salesperson'spersonal assistant at headquarters so that it can be mailed outimmediately. This substantially increases the efficiency of the user(salesperson) and drastically reduces subsequent errors in rememberingand/or relaying the information to the appropriate recipient. Thesalesperson can also choose to review candidate tasks 106 before theyare forwarded to eliminate any undesired tasks.

The candidate tasks 106 can also be utilized to fully perform a desiredtask selected by a user. These instances, discussed in detail infra,allow execution and/or guidance of the task rather than just calling upan application and then requiring the user to enter the information.Additional information can also be incorporated with the executed taskto allow a user to quickly ascertain why a task was performed. Forexample, a hyperlink can be provided in a calendar entry that brings upthe date and time and who the call was placed with for that particularmeeting scheduling. This eliminates unnecessary guessing as to theorigination of, for example, a meeting request. Thus, the taskrecognition system 100 can be employed to substantially reduce theamount of time and effort in fulfilling tasks mentioned duringcommunications while substantially reducing errors as well by reducingreliance on a user's memory of events.

Turning to FIG. 2, another block diagram of a task recognition system200 for communications in accordance with an aspect of an embodiment isdepicted. The task recognition system 200 is comprised of task assistantcomponent 202 that receives communications 204 and provides candidatetasks 206. The task assistant component 202 is comprised of an intentrecognition component 208 and a candidate task component 210. Thecommunications 204 can include, but are not limited to, voicecommunications and/or written communications and the like such as, forexample, emailing, instant messaging, text messaging, telephone calls,etc. The intent recognition component 208 receives the communications204 and dynamically monitors the communications 204 for an apparentintent related to a task.

The recognition of the task intent can be assisted with artificialintelligence techniques such as, for example, natural languageprocessing techniques and the like. The intent recognition component 208determines if a task has been referred to and the intent, if any,regarding accomplishment of the task. The intent is generally construedfor a user who employs the task recognition system 200, but the intentrecognition component 208 can also be utilized to determine intent forone or multiple parties in the communications 204. Thus, the taskrecognition system 200 can be utilized to provide candidate tasks 206 tomultiple users based on their individual intents and/or tasks.

As an example, the intent recognition component 208 can dynamicallyrecognize a phrase such as “schedule a meeting on Wednesday” and candetermine, for example, if user A is the party that will do thescheduling (e.g. user A states “yes, I'll schedule that”). Thus, user Acan be presented with a candidate task for scheduling the meeting. Theintent recognition component 208 can also employ contextual and/orenvironmental information to assist in assessing tasks and/or intent.For example, time-of-day can be utilized to determine when a userintends to do a task. Thus, if the time is 11 am and the user refers tocompleting the task “by 10,” they are most likely referring to 10 pm andnot 10 am. Similarly, environmental information such as whether the useris on the phone, on the computer, in the office or in a car, etc., canbe utilized to facilitate determination of the intention of the userassociated with a task. This substantially increases the accuracy of theintent recognition component 208.

Although the intent recognition component 208 is illustrated within thetask assistant component 202, other instances can employ external and/orpre-existing recognition components as well. This increases theflexibility of the task recognition system 200 and allows for easyintegration into existing communication devices and/or systems and thelike. The intent recognition component 208 can employ simplisticrecognizers such as, for example, key phrase recognizers (e.g., usingkey phrase catalogs, etc.) in text and/or voice communications and thelike and/or sophisticated artificial intelligence recognizers. Thisallows the task assistant system 200 to be scaled appropriately based onavailable resources. For example, a PDA device might have very limitedresources and, therefore, a resource efficient recognizer can beemployed by the intent recognition component 208. If the intentrecognition component 208 is located with abundant resources, asubstantially more powerful recognizer can be utilized (e.g., the intentrecognition component 208 is located at a communication service providersuch as a wireless provider with substantially unlimited processingpower that provides the recognition function to an end user, etc.).

The candidate task component 210 receives the task intent from theintent recognition component 208 and associates it with a task. Thus,for example, if the intent recognition component 208 determined that auser intends to schedule a meeting, the candidate task component 210determines what task and/or tasks need to be performed to accomplish it.The tasks for scheduling a meeting can include opening up a calendar andinserting meeting titles, parties to the meeting, times of the meeting,and/or adding additional information such as, for example, a link to whythe meeting was input into the calendar, etc. It can also include a taskto remind the user of the meeting and/or a task to follow-up withanother party to obtain additional information such as their contactinformation to allow completion of the meeting scheduling. Another taskcan include notification of others that a meeting is to take place.Thus, the candidate task component 210 determines what tasks areassociated with the user's intent and provides them as the candidatetasks 206. The candidate tasks 206 can contain, for example, one ormultiple task suggestions that the user can either accept or rejectafter a follow-up prompting.

Looking at FIG. 3, yet another block diagram of a task recognitionsystem 300 for communications in accordance with an aspect of anembodiment is illustrated. The task recognition system 300 is comprisedof task assistant component 302 that receives communications 304 andprovides candidate tasks 306. The task assistant component 302 iscomprised of an intent recognition component 308, a candidate taskcomponent 310, and an action manager component 312. The communications304 can include, but are not limited to, voice communications and/orwritten communications and the like such as, for example, emailing,instant messaging, text messaging, telephone calls, etc. The intentrecognition component 308 receives the communications 304 anddynamically monitors the communications 304 for an apparent intentrelated to a task. The candidate task component 310 receives the taskintent from the intent recognition component 308 and associates it witha task to form stored candidate tasks 314. The stored candidate tasks314 can be stored externally if desired.

The action manager component 312 receives candidate tasks 306 directlyfrom the candidate task component 310 and/or indirectly from thecandidate task component 310 via the stored candidate tasks 314. Theaction manager component 312 utilizes an event trigger to determine whento prompt a user 316 with candidate tasks 306. The event trigger caninclude, but is not limited to, the completion of the communications 304and the like. Thus, for example, when a phone call ends, the actionmanager component 312 can prompt the user 316 with the candidate tasks306 that were determined during the communications 304. The user 316 canthen provide user input 318 to the action manager component 312regarding whether to complete any of the candidate tasks 306. The userinput 318 can also include additional information on how and/or when tocomplete a task and the like. In some instances, the action managercomponent 312 can act as a guide (e.g., as if it is a real lifeassistant sitting next to a user) and query the user 316 as to how toproceed and/or to supply missing/additional information that can berequired to fulfill a task.

The action manager component 312 receives the user input 318 and actsupon any desired tasks. To accomplish this, the action manager component312 can employ action profiles 320. The action profiles 320 represent,for example, templates on how to accomplish various tasks. The actionprofiles 320 can be provided by users, systems, and/or third partiesand, thus, allow for additional flexibility and control over taskcompletion. For example, the action profiles 320 can contain an addressbook profile that indicates how contact information is to be stored in auser's address book (e.g., which software program to use, formatting ofthe name information—last name first, etc., font size, color, etc.). Theaction manager component 312 then carries out a task utilizing anappropriate program from task related applications 322 based on anaction profile if provided. This interaction with the user 316, allowsthe user 316 to maintain control over what, how and/or when the tasksare accomplished.

In another instance, the action manager component 312 can prompt theuser 316 that an intent and/or candidate task has been detected duringthe communications 304. Thus, the action manager component 312 canreceive direct input from the intent recognition component 308 regardingintent if necessary. This can enable the user 316 to monitor theprogress of the task recognition system 300 dynamically. The user 316could select and/or delete the intents and/or candidate tasks insubstantially real time as well.

It can be appreciated that although the components 308-312 of the taskassistant component 302 are illustrated in a co-located manner, they canalso be remotely located and communicate via a variety of communicationmeans. Thus, each component 308-312 can reside in a location that bestsupports its resource requirements and/or user interfaces and the like.Traditionally, complex recognition algorithms have required powerfulprocessing resources. Thus, the intent recognition component 308 can belocated at a service provider and/or on a desk top computing device andthe like while the candidate task component 310 and/or the actionmanager component 312 can reside on, for example, a mobile device andthe like. Likewise, the stored candidate tasks 314 can be stored locallyand/or remotely to facilitate processing of the tasks. Communicationsmeans can include, but are not limited to, global communication systemssuch as the Internet, intranet systems, wireless systems, wired systems(e.g., landlines), fiber-optic systems, and/or satellite-based systemsand the like.

Because of the substantial flexibility of the task recognition system300, it can be completely performed by service providers at theirfacilities, partially performed at their facilities, and/or totallyperformed on a communication device and the like. Revenue based schemescan be employed at any point to allow income based on individualportions of the task recognition system 300. For example, charges canoccur for completed tasks, for providing candidate task lists, and/orfor just recognizing intent in the communications 304 and the like. Thiscan allow a service provider to provide various levels of capabilitiesfor their users and charge accordingly.

Referring to FIG. 4, an example architecture 400 of a task recognitionsystem for communications in accordance with an aspect of an embodimentis shown. The architecture 400 illustrates dynamic voice recognition fora device during a telephone call. Follow-up prompting is initiated basedon various activities/trigger events. It can be appreciated thatalthough the example architecture 400 illustrates voice-basedcommunications, other types of communications can be utilized as well,including, but not limited to email, instant messaging, and/or textmessaging and the like.

Given that communication devices are often used in mobile contexts(transit, walking, between meetings, etc.), it is easy for a user totell someone on a phone that they will follow-up by scheduling a meetingor some other action and then forget to do so after they hang up.Instances disclosed herein can allow such a communication device to“listen” for the intent of users regarding a mentioned task during theirconversation, and after the call completes, prompt for further actionbased on those task intents. Phrases like “follow-up,” “schedule ameeting,” “call you tomorrow,” etc. can be construed as an intent by auser to actually commit to performing a certain task. For example, if auser was talking to “Bob” and said “I'll follow up on this tomorrow.”After the call, the communication device can speak the prompt “Would youlike to add a task to follow-up with Bob?” If the user, for example,replies “yes,” a task can be added, perhaps containing a reference tothe call history with the date and time of the just ended call with Bob.

In the example architecture 400 of an example implementation utilizingvoice-based communications, an audio in 402 (from a microphone, headset,etc.) is routed through a task assistant component 404 during a call.The audio stream is forwarded to a regular phone subsystem 418 on acommunication device. In this example, the task assistant component 404employs an external recognizer 408. This allows the task assistantcomponent 404 to utilize existing recognizers and the like withoutrequiring them to be integrated into the task assistant component 404.Thus, the task assistant component 404 channels the audio stream throughthe recognizer 408 as well. The recognizer 408, in this example,utilizes a set of action intentions 410 to facilitate recognition of auser's intent with regard to a task during in-call recognition.

When an action intent is recognized, a subtle audio cue can be givenover an audio out 406 channel to confirm to a user that an actionintention has been recognized. Also, when an action intention isrecognized, an item is added to the action stack 412 by the taskassistant component 404. Typically, upon completion of the call, thecall information is written to a call log 420. In this example, a callcompletion signal is also sent to an action manager component 414(external to the task assistant component 404) when the call iscompleted. The action manager component 414, in this example, pullsitems from the action stack 412 on a first-in, first-out (FIFO) basis.The action manager component 414 then passes the action item to aprofile in an action profile collection 416 corresponding to the currentaction item (in this example, it is “meeting”). The item artifact isthen written to an appropriate store 422 on the communication devicebased on the appropriate action profile. The action manager component414 can do additional prompting by voice and/or other means forinformation needed for the action item. A reference, copy, or link tothe call log information can also be added to the action item.

In another instance, upon completion of a call and hang up, the taskassistant component 404 actually “calls” a user back. It can be alllocal to the communication device and, in that case, the phone ringsitself and when the user answers, the task assistant component 404and/or action manager component 414 guides the user through handlingsome or all of the action items. This experience can be fully verbaland/or a mix of verbal and other interactions.

In view of the exemplary systems shown and described above,methodologies that may be implemented in accordance with the embodimentswill be better appreciated with reference to the flow charts of FIGS. 5and 6. While, for purposes of simplicity of explanation, themethodologies are shown and described as a series of blocks, it is to beunderstood and appreciated that the embodiments are not limited by theorder of the blocks, as some blocks may, in accordance with anembodiment, occur in different orders and/or concurrently with otherblocks from that shown and described herein. Moreover, not allillustrated blocks may be required to implement the methodologies inaccordance with the embodiments.

The embodiments may be described in the general context ofcomputer-executable instructions, such as program modules, executed byone or more components. Generally, program modules include routines,programs, objects, data structures, etc., that perform particular tasksor implement particular abstract data types. Typically, thefunctionality of the program modules may be combined or distributed asdesired in various instances of the embodiments.

In FIG. 5, a flow diagram of a method 500 of facilitating taskrecognition in communications in accordance with an aspect of anembodiment is shown. The method 500 starts 502 by dynamically detectingan apparent intent related to a task while monitoring humancommunications 504. The communications can include, but are not limitedto, voice communications and/or written communications and the like suchas, for example, emailing, instant messaging, text messaging, telephonecalls, etc. Contextual and/or environmental information can also beutilized to more accurately determine a user's intent. This typicallyallows assumptions to be made as to ambiguous references monitored in acommunication. A detected intent is then associated with a task tocreate a candidate task 506. A user intent can require one or more tasksto complete. For example, a user might state “yes, I'll go on the tripwith you” and that might require not only an input to a calendar programas a reminder, but also a task to contact a travel agency and/or requesttickets, a rental car, and/or a hotel and the like. A user is thenprompted of the candidate task following a trigger event 508, ending theflow 510. The trigger event can include, for example, the ending of acommunication and/or a particular time of day and the like. Asalesperson for example, might make sales calls during the day andprompting with candidate tasks after each call might slow down the salescalls. At the end of the day, the salesperson can then review theirtasks at one time. Thus, all ordering tasks can be grouped and/or allsupport tasks can be grouped and the like. The candidate task groupingcan substantially enhance the user's productivity.

Looking at FIG. 6, another flow diagram of a method 600 of facilitatingtask recognition in communications in accordance with an aspect of anembodiment is depicted. The method 600 starts 602 by accepting acandidate task selection from a user 604. As noted supra, candidatetasks are presented to a user at an appropriate time, giving the usercontrol over what tasks and when and/or how the tasks are completed. Theselected task is then executed utilizing an action profile and a taskassociated application 606. Action profiles can be supplied by thirdparties such as, for example, the providers of the task associatedapplication and the like.

The action profiles can also be supplied by a user to allowpersonalization of how and/or when various tasks are performed and thelike. The action profiles allow substantial flexibility to be easilyincorporated into the process. The user is then provided with avisualization of the executed task that includes information relating toan origin of the task 608, ending the flow 610. For example, a user ispresented with a completed calendar entry with a hyperlink linking towhen a communication occurred, who the communication was with, and/orthe length of the communication. This can assist a user in rememberingwhy the calendar entry was made.

It can be appreciated that although visualization of the executed taskis commonly performed, other means of relaying task related informationcan be employed as well in other instances. These can include, but arenot limited to, audible means such as calling a user and indicating whenand where a meeting will take place and the like. Likewise, a user canbe prompted with a candidate task selection list via a voice call wherethe user can accept and/or deny various tasks via voice responses andthe like.

FIG. 7 is a block diagram of a sample environment 700 with whichembodiments can interact. It can be appreciated that various componentsof instances provided herein can be distributed and utilize such anenvironment to interact with each other. The system 700 furtherillustrates a communication means that includes one or more client(s)702. The client(s) 702 can be hardware and/or software (e.g., threads,processes, computing devices). The system 700 also includes one or moreserver(s) 704. The server(s) 704 can also be hardware and/or software(e.g., threads, processes, computing devices). One possiblecommunication between a client 702 and a server 704 can be in the formof a data packet adapted to be transmitted between two or more computerprocesses. The system 700 includes a communication framework 708 thatcan be employed to facilitate communications between the client(s) 702and the server(s) 704. The client(s) 702 are connected to one or moreclient data store(s) 710 that can be employed to store information localto the client(s) 702. Similarly, the server(s) 704 are connected to oneor more server data store(s) 706 that can be employed to storeinformation local to the server(s) 704.

It is to be appreciated that the systems and/or methods of theembodiments can be utilized in task recognition facilitating computercomponents and non-computer related components alike. Further, thoseskilled in the art will recognize that the systems and/or methods of theembodiments are employable in a vast array of electronic relatedtechnologies, including, but not limited to, computers, servers and/orhandheld electronic devices, and the like.

What has been described above includes examples of the embodiments. Itis, of course, not possible to describe every conceivable combination ofcomponents or methodologies for purposes of describing the embodiments,but one of ordinary skill in the art may recognize that many furthercombinations and permutations of the embodiments are possible.Accordingly, the subject matter is intended to embrace all suchalterations, modifications and variations that fall within the spiritand scope of the appended claims. Furthermore, to the extent that theterm “includes” is used in either the detailed description or theclaims, such term is intended to be inclusive in a manner similar to theterm “comprising” as “comprising” is interpreted when employed as atransitional word in a claim.

1. A computer-implemented system that responds to human communications,comprising: a recognition component that dynamically monitors humancommunications for an apparent intent related to a task discussed by auser during a communication session with a human second party; a taskcomponent that receives, at least in part, an apparent intent from therecognition component and associates it with a task to form a candidatetask for prompting a user; and a computer readable storage mediumcomprising data structures and sets of codes for causing a computer toexecute the recognition and task components.
 2. The computer-implementedsystem of claim 1, the recognition component incorporates environmentalor contextual information to facilitate in determining an apparentintent.
 3. The computer-implemented system of claim 1, the recognitioncomponent employs, at least in part, artificial intelligence processingto detect an apparent intent in the communications.
 4. Thecomputer-implemented system of claim 1, the task component storescandidate tasks for recall after a trigger event.
 5. Thecomputer-implemented system of claim 1, the task component orrecognition component is/are remotely located to a device utilized forthe communications.
 6. The computer-implemented system of claim 1, thecommunications comprising audio communications.
 7. Thecomputer-implemented system of claim 1 further comprising: an actionmanager component that receives a candidate task directly or indirectlyfrom the task component and prompts a user about the candidate task. 8.The computer-implemented system of claim 7, the action manager componentprompts the user after a trigger event.
 9. The computer-implementedsystem of claim 8, the trigger event comprising detection of theapparent intent related to a task and completion of the communications.10. The computer-implemented system of claim 7, the action managercomponent interacts with a user to determine which candidate task isperformed.
 11. The computer-implemented system of claim 10, the actionmanager component employs an action profile to facilitate in completinga task.
 12. The computer-implemented system of claim 10, the actionmanager component adds a reference, a copy, or a link associated with anoriginating communication in an application associated with a performedtask.
 13. The computer-implemented system of claim 10, the actionmanager component interacts with the user to determine which candidatetask is performed by spoken communication.
 14. The computer-implementedsystem of claim 10, the action manager component interacts with the userby prompting with a list of candidate task actions and receiving a userinput to select which actions to perform.
 15. The computer-implementedsystem of claim 10, the action manager component interacts with the userby prompting with a candidate task action and guides the user to supplymissing information to complete the task action.
 16. Thecomputer-implemented system of claim 7, the action manager component isremotely located to a device utilized for the communications.
 17. Thecomputer-implemented system of claim 7, the action manager componentprompts a user other than participants of the communications.
 18. Thecomputer-implemented system of claim 7, the action manager componentcontacts a user subsequent to a completion of communications via asimilar communication means utilized for the communications to promptfor a follow up to the candidate task.
 19. The computer-implementedsystem of claim 1, wherein the recognition component monitors spokenhuman communications.
 20. The computer-implemented system of claim 19,wherein the recognition component monitors wireless communication of amobile device used by the user for spoken human communications.
 21. Thecomputer-implemented system of claim 20, further comprising an actionmanager component that receives a candidate task and prompts the userabout the candidate task after completion of the communication sessionby calling back the user on the mobile device.
 22. Thecomputer-implemented system of claim 20, wherein the action managerresides on service provider network in wireless communication with themobile device.
 23. The computer-implemented system of claim 1, whereinthe recognition component monitors textual human communications.
 24. Thecomputer-implemented system of claim 1, further comprising therecognition component that dynamically monitors human communications forthe apparent intent of a sales transaction task and the task componentthat associates the second party with the sales transaction task. 25.The computer-implemented system of claim 1, further comprising therecognition component that dynamically monitors human communications forthe apparent intent of a trip task and the task component thatassociates the trip task with a calendar input and prompts forassociated travel and lodging tasks.
 26. The computer-implemented systemof claim 1, further comprising the recognition component for performingphrase recognition to determining apparent intent.
 27. Thecomputer-implemented system of claim 26, further comprising therecognition component for utilizing contextual or environmentalinformation to assist in determining meaning of the human communicationscomprising time of day, day of week, and device used by the user toperform the human communications.
 28. The computer-implemented system ofclaim 1, further comprising the recognition component for excluding acandidate task action based upon a response from the human second party.29. The computer-implemented system of claim 1, the communicationscomprising visual communications.
 30. The computer-implemented system ofclaim 1, the communications comprising written communications.
 31. Acomputer-implemented method for extracting tasks from communications,comprising: dynamically detecting an apparent intent related to a taskwhile monitoring human communications by a user during a communicationsession with a human second party; associating a detected intent with atask to create a candidate task; and prompting a user of the candidatetask following a trigger event.
 32. The computer-implemented method ofclaim 31 further comprising: accepting a candidate task selection fromthe user; executing the selected task utilizing an action profile and atask associated application; and providing the user with a visualizationof the executed task that includes information relating to an origin ofthe task.
 33. The computer-implemented method of claim 31 furthercomprising: employing environmental or contextual information tofacilitate in determining an apparent intent.
 34. The method of claim33, further comprising: dynamically detecting an apparent intent relatedto a task while monitoring a human communication session between a userand a second party over a communication network by performing phraserecognition of spoken or textual content, the dynamic detecting assistedby the contextual or environmental information of time of day, day ofthe week, and device used by the user for the human communicationsession; prompting the user with the candidate task following thetrigger event of termination of the communication session forconfirmation of a candidate task associated with the detected intent;and storing a confirmed task referenced to context of the humancommunication session in a computer-readable storage medium forexecution by an application on a computer for the user.
 35. Thecomputer-implemented method of claim 31, the communications comprisingemails, instant messaging, text messaging, or voice communications. 36.A computer-implemented system that is responsive to humancommunications, comprising: means for dynamically extracting an apparentintent related to a task from visual or aural communications discussedby a user during a communication session with a human second party;means for associating the extracted apparent intent to an existing taskto create a candidate task; means for interacting with the user toindicate that a candidate task was obtained from the communications andto allow user selections of candidate tasks for execution; and acomputer readable storage medium comprising data structures and sets ofcodes for causing a computer to execute the recognition and taskcomponents.